PENGELOMPOKKAN DATA MINING PADA JUMLAH PENUMPANG DI BANDARA HANG NADIM - Koko Handoko (Universitas Putera Batam, 2018)
The concept of data mining becomes one of the important tools in information management because the existing information has an increasing number. Data mining has many techniques in practice, one of which is the clustering technique which is the process of grouping data into groups so that data exist in the same group have properties as closely as possible. Clustering has many different methods, one of which is K-Means. By using ata mining clustering on traffic activity data taken from Hang Nadim Airport Batam, it can be obtained by grouping passenger based on clusters according to the nature of each data. The data taken include the number of passengers coming, departing, and transiting. In the process of performing data mining clustering, existing sample data must go through several important stages in order to get the correct cluster results. Stages that must be passed the Stages of Data Processing, Clustering Stage and Stage Algorithm. Based on the results of research that has been done on the existing sample data, it can be concluded the results of data grouping of passengers at Hang Nadim Airport Batam.